CiteExport$(function(){PrimeFaces.cw("TieredMenu","widget_formSmash_upper_j_idt144",{id:"formSmash:upper:j_idt144",widgetVar:"widget_formSmash_upper_j_idt144",autoDisplay:true,overlay:true,my:"left top",at:"left bottom",trigger:"formSmash:upper:exportLink",triggerEvent:"click"});}); $(function(){PrimeFaces.cw("OverlayPanel","widget_formSmash_upper_j_idt145_j_idt147",{id:"formSmash:upper:j_idt145:j_idt147",widgetVar:"widget_formSmash_upper_j_idt145_j_idt147",target:"formSmash:upper:j_idt145:permLink",showEffect:"blind",hideEffect:"fade",my:"right top",at:"right bottom",showCloseIcon:true});});

On Solving Singular Diffusion Equations With Monte Carlo MethodsPrimeFaces.cw("AccordionPanel","widget_formSmash_some",{id:"formSmash:some",widgetVar:"widget_formSmash_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_all",{id:"formSmash:all",widgetVar:"widget_formSmash_all",multiple:true});
function selectAll()
{
var panelSome = $(PrimeFaces.escapeClientId("formSmash:some"));
var panelAll = $(PrimeFaces.escapeClientId("formSmash:all"));
panelAll.toggle();
toggleList(panelSome.get(0).childNodes, panelAll);
toggleList(panelAll.get(0).childNodes, panelAll);
}
/*Toggling the list of authorPanel nodes according to the toggling of the closeable second panel */
function toggleList(childList, panel)
{
var panelWasOpen = (panel.get(0).style.display == 'none');
// console.log('panel was open ' + panelWasOpen);
for (var c = 0; c < childList.length; c++) {
if (childList[c].classList.contains('authorPanel')) {
clickNode(panelWasOpen, childList[c]);
}
}
}
/*nodes have styleClass ui-corner-top if they are expanded and ui-corner-all if they are collapsed */
function clickNode(collapse, child)
{
if (collapse && child.classList.contains('ui-corner-top')) {
// console.log('collapse');
child.click();
}
if (!collapse && child.classList.contains('ui-corner-all')) {
// console.log('expand');
child.click();
}
}
PrimeFaces.cw("AccordionPanel","widget_formSmash_responsibleOrgs",{id:"formSmash:responsibleOrgs",widgetVar:"widget_formSmash_responsibleOrgs",multiple:true}); 2010 (English)In: IEEE Transactions on Plasma Science, ISSN 0093-3813, E-ISSN 1939-9375, Vol. 38, no 9, p. 2185-2189Article in journal (Refereed) Published
##### Abstract [en]

##### Place, publisher, year, edition, pages

2010. Vol. 38, no 9, p. 2185-2189
##### Keyword [en]

Diffusion equations, Monte Carlo methods, simulation, stochastic differential equations
##### National Category

Physical Sciences
##### Identifiers

URN: urn:nbn:se:kth:diva-27684DOI: 10.1109/TPS.2010.2057259ISI: 000283252500014Scopus ID: 2-s2.0-77956617100OAI: oai:DiVA.org:kth-27684DiVA, id: diva2:380424
#####

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt467",{id:"formSmash:j_idt467",widgetVar:"widget_formSmash_j_idt467",multiple:true});
#####

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt473",{id:"formSmash:j_idt473",widgetVar:"widget_formSmash_j_idt473",multiple:true});
#####

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt479",{id:"formSmash:j_idt479",widgetVar:"widget_formSmash_j_idt479",multiple:true});
##### Note

QC 20101221Available from: 2010-12-21 Created: 2010-12-20 Last updated: 2017-12-11Bibliographically approved
##### In thesis

Diffusion equations in one, two, or three dimensions with inhomogeneous diffusion coefficients are usually solved with finite-difference or finite-element methods. For higher dimensional problems, Monte Carlo solutions to the corresponding stochastic differential equations can be more effective. The inhomogeneities of the diffusion constants restrict the time steps. When the coefficient in front of the highest derivative of the corresponding differential equation goes to zero, the equation is said to be singular. For a 1-D stochastic differential equation, this corresponds to the diffusion coefficient that goes to zero, making the coefficient strongly inhomogeneous, which, however, is a natural condition when the process is limited to a region in phase space. The standard methods to solve stochastic differential equations near the boundaries are to reduce the time step and to use reflection. The strong inhomogeneity at the boundary will strongly limit the time steps. To allow for longer time steps for Monte Carlo codes, higher order methods have been developed with better convergence in phase space. The aim of our investigation is to find operators producing converged results for large time steps for higher dimensional problems. Here, we compare new and standard algorithms with known steady-state solutions.

1. On Monte Carlo Operators for Studying Collisional Relaxation in Toroidal Plasmas$(function(){PrimeFaces.cw("OverlayPanel","overlay615851",{id:"formSmash:j_idt787:0:j_idt791",widgetVar:"overlay615851",target:"formSmash:j_idt787:0:parentLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

doi
urn-nbn$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_j_idt1256",{id:"formSmash:j_idt1256",widgetVar:"widget_formSmash_j_idt1256",showEffect:"fade",hideEffect:"fade",showDelay:500,hideDelay:300,target:"formSmash:altmetricDiv"});});

CiteExport$(function(){PrimeFaces.cw("TieredMenu","widget_formSmash_lower_j_idt1309",{id:"formSmash:lower:j_idt1309",widgetVar:"widget_formSmash_lower_j_idt1309",autoDisplay:true,overlay:true,my:"left top",at:"left bottom",trigger:"formSmash:lower:exportLink",triggerEvent:"click"});}); $(function(){PrimeFaces.cw("OverlayPanel","widget_formSmash_lower_j_idt1310_j_idt1312",{id:"formSmash:lower:j_idt1310:j_idt1312",widgetVar:"widget_formSmash_lower_j_idt1310_j_idt1312",target:"formSmash:lower:j_idt1310:permLink",showEffect:"blind",hideEffect:"fade",my:"right top",at:"right bottom",showCloseIcon:true});});